AI Engineer (GEnAI, AWS Bedrock, AWS AI Certification)

This job description for an AI Engineer focuseson the design, development, and deployment of intelligent applicationsusing Amazon Web Services (AWS), Python, and advanced LargeLanguage Model (LLM) techniques like Retrieval-Augmented Generation(RAG). 

Core Responsibilities

• LLM Integration & Orchestration: Design and build production-grade applications leveraging LLMs from providers like Amazon Bedrock (e.g., Anthropic Claude, Amazon Nova) or open-source models (Llama, Mistral).
• RAG Pipeline Development: Implement and optimize Retrieval-Augmented Generation (RAG) workflows, including document parsing, semantic chunking, and embedding generation.
• Vector Database Management: Manage and query vector stores such as Amazon OpenSearch Service, Pinecone, or FAISS to enable efficient semantic retrieval.
• Agentic Workflows: Develop autonomous AI agents capable of tool-calling, multi-step reasoning, and complex task orchestration using frameworks like LangChain or LangGraph.
• Deployment & MLOps: Containerize AI services using Docker and deploy them on AWS infrastructure (e.g., Lambda, ECS, SageMaker) with robust CI/CD pipelines.
• Performance Tuning: Optimize model outputs through prompt engineering, fine-tuning (LoRA/PEFT), and managing latency and cost efficiency. 

Technical Requirements

• Programming: Proficiency in Python is essential, specifically for developing scalable backend services and AI logic.
• AWS Ecosystem: Hands-on experience with AWS AI services including Bedrock, SageMaker AI, Lambda, S3, and API Gateway.
• AI Frameworks: Deep experience with LangChain, LlamaIndex, and deep learning libraries like PyTorch or TensorFlow.
• API Development: Skill in building and integrating RESTful APIs (e.g., FastAPI, Flask) to connect AI capabilities to enterprise systems.
• Security & Governance: Understanding of Responsible AI practices, including guardrails against hallucinations and ensuring data privacy (GDPR/SOC2). 

Preferred Qualifications

• Cloud Certification: AWS Certified Generative AI Developer - Professional or AWS Certified Machine Learning - Specialty.
• Bachelor degree in computer science or related field.